inception_v3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\sunsh\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\tqdm\\auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
      "  from .autonotebook import tqdm as notebook_tqdm\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torch.nn as nn\n",
    "import torchvision\n",
    "from torchinfo import summary         \n",
    "import numpy as np\n",
    "import torchvision.transforms as tf\n",
    "import transformers                    \n",
    "from tensorboardX import SummaryWriter \n",
    "from pkg_resources import packaging    \n",
    "import matplotlib.pyplot as plt\n",
    "from mpl_toolkits.axes_grid1 import ImageGrid\n",
    "from openTSNE import TSNE              \n",
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "\n",
    "from tqdm import tqdm\n",
    "import random\n",
    "import re\n",
    "import time\n",
    "import math"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Using cache found in C:\\Users\\sunsh/.cache\\torch\\hub\\pytorch_vision_v0.10.0\n",
      "c:\\Users\\sunsh\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
      "  warnings.warn(\n",
      "c:\\Users\\sunsh\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=Inception_V3_Weights.IMAGENET1K_V1`. You can also use `weights=Inception_V3_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "=================================================================\n",
       "Layer (type:depth-idx)                   Param #\n",
       "=================================================================\n",
       "Inception3                               --\n",
       "├─BasicConv2d: 1-1                       --\n",
       "│    └─Conv2d: 2-1                       864\n",
       "│    └─BatchNorm2d: 2-2                  64\n",
       "├─BasicConv2d: 1-2                       --\n",
       "│    └─Conv2d: 2-3                       9,216\n",
       "│    └─BatchNorm2d: 2-4                  64\n",
       "├─BasicConv2d: 1-3                       --\n",
       "│    └─Conv2d: 2-5                       18,432\n",
       "│    └─BatchNorm2d: 2-6                  128\n",
       "├─MaxPool2d: 1-4                         --\n",
       "├─BasicConv2d: 1-5                       --\n",
       "│    └─Conv2d: 2-7                       5,120\n",
       "│    └─BatchNorm2d: 2-8                  160\n",
       "├─BasicConv2d: 1-6                       --\n",
       "│    └─Conv2d: 2-9                       138,240\n",
       "│    └─BatchNorm2d: 2-10                 384\n",
       "├─MaxPool2d: 1-7                         --\n",
       "├─InceptionA: 1-8                        --\n",
       "│    └─BasicConv2d: 2-11                 --\n",
       "│    │    └─Conv2d: 3-1                  12,288\n",
       "│    │    └─BatchNorm2d: 3-2             128\n",
       "│    └─BasicConv2d: 2-12                 --\n",
       "│    │    └─Conv2d: 3-3                  9,216\n",
       "│    │    └─BatchNorm2d: 3-4             96\n",
       "│    └─BasicConv2d: 2-13                 --\n",
       "│    │    └─Conv2d: 3-5                  76,800\n",
       "│    │    └─BatchNorm2d: 3-6             128\n",
       "│    └─BasicConv2d: 2-14                 --\n",
       "│    │    └─Conv2d: 3-7                  12,288\n",
       "│    │    └─BatchNorm2d: 3-8             128\n",
       "│    └─BasicConv2d: 2-15                 --\n",
       "│    │    └─Conv2d: 3-9                  55,296\n",
       "│    │    └─BatchNorm2d: 3-10            192\n",
       "│    └─BasicConv2d: 2-16                 --\n",
       "│    │    └─Conv2d: 3-11                 82,944\n",
       "│    │    └─BatchNorm2d: 3-12            192\n",
       "│    └─BasicConv2d: 2-17                 --\n",
       "│    │    └─Conv2d: 3-13                 6,144\n",
       "│    │    └─BatchNorm2d: 3-14            64\n",
       "├─InceptionA: 1-9                        --\n",
       "│    └─BasicConv2d: 2-18                 --\n",
       "│    │    └─Conv2d: 3-15                 16,384\n",
       "│    │    └─BatchNorm2d: 3-16            128\n",
       "│    └─BasicConv2d: 2-19                 --\n",
       "│    │    └─Conv2d: 3-17                 12,288\n",
       "│    │    └─BatchNorm2d: 3-18            96\n",
       "│    └─BasicConv2d: 2-20                 --\n",
       "│    │    └─Conv2d: 3-19                 76,800\n",
       "│    │    └─BatchNorm2d: 3-20            128\n",
       "│    └─BasicConv2d: 2-21                 --\n",
       "│    │    └─Conv2d: 3-21                 16,384\n",
       "│    │    └─BatchNorm2d: 3-22            128\n",
       "│    └─BasicConv2d: 2-22                 --\n",
       "│    │    └─Conv2d: 3-23                 55,296\n",
       "│    │    └─BatchNorm2d: 3-24            192\n",
       "│    └─BasicConv2d: 2-23                 --\n",
       "│    │    └─Conv2d: 3-25                 82,944\n",
       "│    │    └─BatchNorm2d: 3-26            192\n",
       "│    └─BasicConv2d: 2-24                 --\n",
       "│    │    └─Conv2d: 3-27                 16,384\n",
       "│    │    └─BatchNorm2d: 3-28            128\n",
       "├─InceptionA: 1-10                       --\n",
       "│    └─BasicConv2d: 2-25                 --\n",
       "│    │    └─Conv2d: 3-29                 18,432\n",
       "│    │    └─BatchNorm2d: 3-30            128\n",
       "│    └─BasicConv2d: 2-26                 --\n",
       "│    │    └─Conv2d: 3-31                 13,824\n",
       "│    │    └─BatchNorm2d: 3-32            96\n",
       "│    └─BasicConv2d: 2-27                 --\n",
       "│    │    └─Conv2d: 3-33                 76,800\n",
       "│    │    └─BatchNorm2d: 3-34            128\n",
       "│    └─BasicConv2d: 2-28                 --\n",
       "│    │    └─Conv2d: 3-35                 18,432\n",
       "│    │    └─BatchNorm2d: 3-36            128\n",
       "│    └─BasicConv2d: 2-29                 --\n",
       "│    │    └─Conv2d: 3-37                 55,296\n",
       "│    │    └─BatchNorm2d: 3-38            192\n",
       "│    └─BasicConv2d: 2-30                 --\n",
       "│    │    └─Conv2d: 3-39                 82,944\n",
       "│    │    └─BatchNorm2d: 3-40            192\n",
       "│    └─BasicConv2d: 2-31                 --\n",
       "│    │    └─Conv2d: 3-41                 18,432\n",
       "│    │    └─BatchNorm2d: 3-42            128\n",
       "├─InceptionB: 1-11                       --\n",
       "│    └─BasicConv2d: 2-32                 --\n",
       "│    │    └─Conv2d: 3-43                 995,328\n",
       "│    │    └─BatchNorm2d: 3-44            768\n",
       "│    └─BasicConv2d: 2-33                 --\n",
       "│    │    └─Conv2d: 3-45                 18,432\n",
       "│    │    └─BatchNorm2d: 3-46            128\n",
       "│    └─BasicConv2d: 2-34                 --\n",
       "│    │    └─Conv2d: 3-47                 55,296\n",
       "│    │    └─BatchNorm2d: 3-48            192\n",
       "│    └─BasicConv2d: 2-35                 --\n",
       "│    │    └─Conv2d: 3-49                 82,944\n",
       "│    │    └─BatchNorm2d: 3-50            192\n",
       "├─InceptionC: 1-12                       --\n",
       "│    └─BasicConv2d: 2-36                 --\n",
       "│    │    └─Conv2d: 3-51                 147,456\n",
       "│    │    └─BatchNorm2d: 3-52            384\n",
       "│    └─BasicConv2d: 2-37                 --\n",
       "│    │    └─Conv2d: 3-53                 98,304\n",
       "│    │    └─BatchNorm2d: 3-54            256\n",
       "│    └─BasicConv2d: 2-38                 --\n",
       "│    │    └─Conv2d: 3-55                 114,688\n",
       "│    │    └─BatchNorm2d: 3-56            256\n",
       "│    └─BasicConv2d: 2-39                 --\n",
       "│    │    └─Conv2d: 3-57                 172,032\n",
       "│    │    └─BatchNorm2d: 3-58            384\n",
       "│    └─BasicConv2d: 2-40                 --\n",
       "│    │    └─Conv2d: 3-59                 98,304\n",
       "│    │    └─BatchNorm2d: 3-60            256\n",
       "│    └─BasicConv2d: 2-41                 --\n",
       "│    │    └─Conv2d: 3-61                 114,688\n",
       "│    │    └─BatchNorm2d: 3-62            256\n",
       "│    └─BasicConv2d: 2-42                 --\n",
       "│    │    └─Conv2d: 3-63                 114,688\n",
       "│    │    └─BatchNorm2d: 3-64            256\n",
       "│    └─BasicConv2d: 2-43                 --\n",
       "│    │    └─Conv2d: 3-65                 114,688\n",
       "│    │    └─BatchNorm2d: 3-66            256\n",
       "│    └─BasicConv2d: 2-44                 --\n",
       "│    │    └─Conv2d: 3-67                 172,032\n",
       "│    │    └─BatchNorm2d: 3-68            384\n",
       "│    └─BasicConv2d: 2-45                 --\n",
       "│    │    └─Conv2d: 3-69                 147,456\n",
       "│    │    └─BatchNorm2d: 3-70            384\n",
       "├─InceptionC: 1-13                       --\n",
       "│    └─BasicConv2d: 2-46                 --\n",
       "│    │    └─Conv2d: 3-71                 147,456\n",
       "│    │    └─BatchNorm2d: 3-72            384\n",
       "│    └─BasicConv2d: 2-47                 --\n",
       "│    │    └─Conv2d: 3-73                 122,880\n",
       "│    │    └─BatchNorm2d: 3-74            320\n",
       "│    └─BasicConv2d: 2-48                 --\n",
       "│    │    └─Conv2d: 3-75                 179,200\n",
       "│    │    └─BatchNorm2d: 3-76            320\n",
       "│    └─BasicConv2d: 2-49                 --\n",
       "│    │    └─Conv2d: 3-77                 215,040\n",
       "│    │    └─BatchNorm2d: 3-78            384\n",
       "│    └─BasicConv2d: 2-50                 --\n",
       "│    │    └─Conv2d: 3-79                 122,880\n",
       "│    │    └─BatchNorm2d: 3-80            320\n",
       "│    └─BasicConv2d: 2-51                 --\n",
       "│    │    └─Conv2d: 3-81                 179,200\n",
       "│    │    └─BatchNorm2d: 3-82            320\n",
       "│    └─BasicConv2d: 2-52                 --\n",
       "│    │    └─Conv2d: 3-83                 179,200\n",
       "│    │    └─BatchNorm2d: 3-84            320\n",
       "│    └─BasicConv2d: 2-53                 --\n",
       "│    │    └─Conv2d: 3-85                 179,200\n",
       "│    │    └─BatchNorm2d: 3-86            320\n",
       "│    └─BasicConv2d: 2-54                 --\n",
       "│    │    └─Conv2d: 3-87                 215,040\n",
       "│    │    └─BatchNorm2d: 3-88            384\n",
       "│    └─BasicConv2d: 2-55                 --\n",
       "│    │    └─Conv2d: 3-89                 147,456\n",
       "│    │    └─BatchNorm2d: 3-90            384\n",
       "├─InceptionC: 1-14                       --\n",
       "│    └─BasicConv2d: 2-56                 --\n",
       "│    │    └─Conv2d: 3-91                 147,456\n",
       "│    │    └─BatchNorm2d: 3-92            384\n",
       "│    └─BasicConv2d: 2-57                 --\n",
       "│    │    └─Conv2d: 3-93                 122,880\n",
       "│    │    └─BatchNorm2d: 3-94            320\n",
       "│    └─BasicConv2d: 2-58                 --\n",
       "│    │    └─Conv2d: 3-95                 179,200\n",
       "│    │    └─BatchNorm2d: 3-96            320\n",
       "│    └─BasicConv2d: 2-59                 --\n",
       "│    │    └─Conv2d: 3-97                 215,040\n",
       "│    │    └─BatchNorm2d: 3-98            384\n",
       "│    └─BasicConv2d: 2-60                 --\n",
       "│    │    └─Conv2d: 3-99                 122,880\n",
       "│    │    └─BatchNorm2d: 3-100           320\n",
       "│    └─BasicConv2d: 2-61                 --\n",
       "│    │    └─Conv2d: 3-101                179,200\n",
       "│    │    └─BatchNorm2d: 3-102           320\n",
       "│    └─BasicConv2d: 2-62                 --\n",
       "│    │    └─Conv2d: 3-103                179,200\n",
       "│    │    └─BatchNorm2d: 3-104           320\n",
       "│    └─BasicConv2d: 2-63                 --\n",
       "│    │    └─Conv2d: 3-105                179,200\n",
       "│    │    └─BatchNorm2d: 3-106           320\n",
       "│    └─BasicConv2d: 2-64                 --\n",
       "│    │    └─Conv2d: 3-107                215,040\n",
       "│    │    └─BatchNorm2d: 3-108           384\n",
       "│    └─BasicConv2d: 2-65                 --\n",
       "│    │    └─Conv2d: 3-109                147,456\n",
       "│    │    └─BatchNorm2d: 3-110           384\n",
       "├─InceptionC: 1-15                       --\n",
       "│    └─BasicConv2d: 2-66                 --\n",
       "│    │    └─Conv2d: 3-111                147,456\n",
       "│    │    └─BatchNorm2d: 3-112           384\n",
       "│    └─BasicConv2d: 2-67                 --\n",
       "│    │    └─Conv2d: 3-113                147,456\n",
       "│    │    └─BatchNorm2d: 3-114           384\n",
       "│    └─BasicConv2d: 2-68                 --\n",
       "│    │    └─Conv2d: 3-115                258,048\n",
       "│    │    └─BatchNorm2d: 3-116           384\n",
       "│    └─BasicConv2d: 2-69                 --\n",
       "│    │    └─Conv2d: 3-117                258,048\n",
       "│    │    └─BatchNorm2d: 3-118           384\n",
       "│    └─BasicConv2d: 2-70                 --\n",
       "│    │    └─Conv2d: 3-119                147,456\n",
       "│    │    └─BatchNorm2d: 3-120           384\n",
       "│    └─BasicConv2d: 2-71                 --\n",
       "│    │    └─Conv2d: 3-121                258,048\n",
       "│    │    └─BatchNorm2d: 3-122           384\n",
       "│    └─BasicConv2d: 2-72                 --\n",
       "│    │    └─Conv2d: 3-123                258,048\n",
       "│    │    └─BatchNorm2d: 3-124           384\n",
       "│    └─BasicConv2d: 2-73                 --\n",
       "│    │    └─Conv2d: 3-125                258,048\n",
       "│    │    └─BatchNorm2d: 3-126           384\n",
       "│    └─BasicConv2d: 2-74                 --\n",
       "│    │    └─Conv2d: 3-127                258,048\n",
       "│    │    └─BatchNorm2d: 3-128           384\n",
       "│    └─BasicConv2d: 2-75                 --\n",
       "│    │    └─Conv2d: 3-129                147,456\n",
       "│    │    └─BatchNorm2d: 3-130           384\n",
       "├─InceptionAux: 1-16                     --\n",
       "│    └─BasicConv2d: 2-76                 --\n",
       "│    │    └─Conv2d: 3-131                98,304\n",
       "│    │    └─BatchNorm2d: 3-132           256\n",
       "│    └─BasicConv2d: 2-77                 --\n",
       "│    │    └─Conv2d: 3-133                2,457,600\n",
       "│    │    └─BatchNorm2d: 3-134           1,536\n",
       "│    └─Linear: 2-78                      769,000\n",
       "├─InceptionD: 1-17                       --\n",
       "│    └─BasicConv2d: 2-79                 --\n",
       "│    │    └─Conv2d: 3-135                147,456\n",
       "│    │    └─BatchNorm2d: 3-136           384\n",
       "│    └─BasicConv2d: 2-80                 --\n",
       "│    │    └─Conv2d: 3-137                552,960\n",
       "│    │    └─BatchNorm2d: 3-138           640\n",
       "│    └─BasicConv2d: 2-81                 --\n",
       "│    │    └─Conv2d: 3-139                147,456\n",
       "│    │    └─BatchNorm2d: 3-140           384\n",
       "│    └─BasicConv2d: 2-82                 --\n",
       "│    │    └─Conv2d: 3-141                258,048\n",
       "│    │    └─BatchNorm2d: 3-142           384\n",
       "│    └─BasicConv2d: 2-83                 --\n",
       "│    │    └─Conv2d: 3-143                258,048\n",
       "│    │    └─BatchNorm2d: 3-144           384\n",
       "│    └─BasicConv2d: 2-84                 --\n",
       "│    │    └─Conv2d: 3-145                331,776\n",
       "│    │    └─BatchNorm2d: 3-146           384\n",
       "├─InceptionE: 1-18                       --\n",
       "│    └─BasicConv2d: 2-85                 --\n",
       "│    │    └─Conv2d: 3-147                409,600\n",
       "│    │    └─BatchNorm2d: 3-148           640\n",
       "│    └─BasicConv2d: 2-86                 --\n",
       "│    │    └─Conv2d: 3-149                491,520\n",
       "│    │    └─BatchNorm2d: 3-150           768\n",
       "│    └─BasicConv2d: 2-87                 --\n",
       "│    │    └─Conv2d: 3-151                442,368\n",
       "│    │    └─BatchNorm2d: 3-152           768\n",
       "│    └─BasicConv2d: 2-88                 --\n",
       "│    │    └─Conv2d: 3-153                442,368\n",
       "│    │    └─BatchNorm2d: 3-154           768\n",
       "│    └─BasicConv2d: 2-89                 --\n",
       "│    │    └─Conv2d: 3-155                573,440\n",
       "│    │    └─BatchNorm2d: 3-156           896\n",
       "│    └─BasicConv2d: 2-90                 --\n",
       "│    │    └─Conv2d: 3-157                1,548,288\n",
       "│    │    └─BatchNorm2d: 3-158           768\n",
       "│    └─BasicConv2d: 2-91                 --\n",
       "│    │    └─Conv2d: 3-159                442,368\n",
       "│    │    └─BatchNorm2d: 3-160           768\n",
       "│    └─BasicConv2d: 2-92                 --\n",
       "│    │    └─Conv2d: 3-161                442,368\n",
       "│    │    └─BatchNorm2d: 3-162           768\n",
       "│    └─BasicConv2d: 2-93                 --\n",
       "│    │    └─Conv2d: 3-163                245,760\n",
       "│    │    └─BatchNorm2d: 3-164           384\n",
       "├─InceptionE: 1-19                       --\n",
       "│    └─BasicConv2d: 2-94                 --\n",
       "│    │    └─Conv2d: 3-165                655,360\n",
       "│    │    └─BatchNorm2d: 3-166           640\n",
       "│    └─BasicConv2d: 2-95                 --\n",
       "│    │    └─Conv2d: 3-167                786,432\n",
       "│    │    └─BatchNorm2d: 3-168           768\n",
       "│    └─BasicConv2d: 2-96                 --\n",
       "│    │    └─Conv2d: 3-169                442,368\n",
       "│    │    └─BatchNorm2d: 3-170           768\n",
       "│    └─BasicConv2d: 2-97                 --\n",
       "│    │    └─Conv2d: 3-171                442,368\n",
       "│    │    └─BatchNorm2d: 3-172           768\n",
       "│    └─BasicConv2d: 2-98                 --\n",
       "│    │    └─Conv2d: 3-173                917,504\n",
       "│    │    └─BatchNorm2d: 3-174           896\n",
       "│    └─BasicConv2d: 2-99                 --\n",
       "│    │    └─Conv2d: 3-175                1,548,288\n",
       "│    │    └─BatchNorm2d: 3-176           768\n",
       "│    └─BasicConv2d: 2-100                --\n",
       "│    │    └─Conv2d: 3-177                442,368\n",
       "│    │    └─BatchNorm2d: 3-178           768\n",
       "│    └─BasicConv2d: 2-101                --\n",
       "│    │    └─Conv2d: 3-179                442,368\n",
       "│    │    └─BatchNorm2d: 3-180           768\n",
       "│    └─BasicConv2d: 2-102                --\n",
       "│    │    └─Conv2d: 3-181                393,216\n",
       "│    │    └─BatchNorm2d: 3-182           384\n",
       "├─AdaptiveAvgPool2d: 1-20                --\n",
       "├─Dropout: 1-21                          --\n",
       "├─Linear: 1-22                           2,049,000\n",
       "=================================================================\n",
       "Total params: 27,161,264\n",
       "Trainable params: 27,161,264\n",
       "Non-trainable params: 0\n",
       "================================================================="
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = torch.hub.load('pytorch/vision:v0.10.0', 'inception_v3', pretrained=True)\n",
    "summary(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Inception3(\n",
       "  (Conv2d_1a_3x3): BasicConv2d(\n",
       "    (conv): Conv2d(3, 32, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
       "    (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  )\n",
       "  (Conv2d_2a_3x3): BasicConv2d(\n",
       "    (conv): Conv2d(32, 32, kernel_size=(3, 3), stride=(1, 1), bias=False)\n",
       "    (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  )\n",
       "  (Conv2d_2b_3x3): BasicConv2d(\n",
       "    (conv): Conv2d(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "    (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  )\n",
       "  (maxpool1): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  (Conv2d_3b_1x1): BasicConv2d(\n",
       "    (conv): Conv2d(64, 80, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "    (bn): BatchNorm2d(80, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  )\n",
       "  (Conv2d_4a_3x3): BasicConv2d(\n",
       "    (conv): Conv2d(80, 192, kernel_size=(3, 3), stride=(1, 1), bias=False)\n",
       "    (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "  )\n",
       "  (maxpool2): MaxPool2d(kernel_size=3, stride=2, padding=0, dilation=1, ceil_mode=False)\n",
       "  (Mixed_5b): InceptionA(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_1): BasicConv2d(\n",
       "      (conv): Conv2d(192, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_2): BasicConv2d(\n",
       "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(192, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(192, 32, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(32, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_5c): InceptionA(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_1): BasicConv2d(\n",
       "      (conv): Conv2d(256, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_2): BasicConv2d(\n",
       "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(256, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_5d): InceptionA(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_1): BasicConv2d(\n",
       "      (conv): Conv2d(288, 48, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(48, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch5x5_2): BasicConv2d(\n",
       "      (conv): Conv2d(48, 64, kernel_size=(5, 5), stride=(1, 1), padding=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_6a): InceptionB(\n",
       "    (branch3x3): BasicConv2d(\n",
       "      (conv): Conv2d(288, 384, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(288, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(64, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(64, 96, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(96, 96, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(96, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_6b): InceptionC(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_2): BasicConv2d(\n",
       "      (conv): Conv2d(128, 128, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_3): BasicConv2d(\n",
       "      (conv): Conv2d(128, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(128, 128, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(128, 128, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_4): BasicConv2d(\n",
       "      (conv): Conv2d(128, 128, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_5): BasicConv2d(\n",
       "      (conv): Conv2d(128, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_6c): InceptionC(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_2): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_3): BasicConv2d(\n",
       "      (conv): Conv2d(160, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_4): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_5): BasicConv2d(\n",
       "      (conv): Conv2d(160, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_6d): InceptionC(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_2): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_3): BasicConv2d(\n",
       "      (conv): Conv2d(160, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 160, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_4): BasicConv2d(\n",
       "      (conv): Conv2d(160, 160, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(160, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_5): BasicConv2d(\n",
       "      (conv): Conv2d(160, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_6e): InceptionC(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_2): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7_3): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_3): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_4): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7dbl_5): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (AuxLogits): InceptionAux(\n",
       "    (conv0): BasicConv2d(\n",
       "      (conv): Conv2d(768, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(128, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (conv1): BasicConv2d(\n",
       "      (conv): Conv2d(128, 768, kernel_size=(5, 5), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(768, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (fc): Linear(in_features=768, out_features=1000, bias=True)\n",
       "  )\n",
       "  (Mixed_7a): InceptionD(\n",
       "    (branch3x3_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_2): BasicConv2d(\n",
       "      (conv): Conv2d(192, 320, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7x3_1): BasicConv2d(\n",
       "      (conv): Conv2d(768, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7x3_2): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(1, 7), stride=(1, 1), padding=(0, 3), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7x3_3): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(7, 1), stride=(1, 1), padding=(3, 0), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch7x7x3_4): BasicConv2d(\n",
       "      (conv): Conv2d(192, 192, kernel_size=(3, 3), stride=(2, 2), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_7b): InceptionE(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(1280, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_1): BasicConv2d(\n",
       "      (conv): Conv2d(1280, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_2a): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_2b): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(1280, 448, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(448, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3a): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3b): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(1280, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (Mixed_7c): InceptionE(\n",
       "    (branch1x1): BasicConv2d(\n",
       "      (conv): Conv2d(2048, 320, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(320, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_1): BasicConv2d(\n",
       "      (conv): Conv2d(2048, 384, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_2a): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3_2b): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_1): BasicConv2d(\n",
       "      (conv): Conv2d(2048, 448, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(448, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_2): BasicConv2d(\n",
       "      (conv): Conv2d(448, 384, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3a): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(1, 3), stride=(1, 1), padding=(0, 1), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch3x3dbl_3b): BasicConv2d(\n",
       "      (conv): Conv2d(384, 384, kernel_size=(3, 1), stride=(1, 1), padding=(1, 0), bias=False)\n",
       "      (bn): BatchNorm2d(384, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "    (branch_pool): BasicConv2d(\n",
       "      (conv): Conv2d(2048, 192, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
       "      (bn): BatchNorm2d(192, eps=0.001, momentum=0.1, affine=True, track_running_stats=True)\n",
       "    )\n",
       "  )\n",
       "  (avgpool): AdaptiveAvgPool2d(output_size=(1, 1))\n",
       "  (dropout): Dropout(p=0.5, inplace=False)\n",
       "  (fc): Linear(in_features=2048, out_features=1000, bias=True)\n",
       ")"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.eval()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Conv2d_1a_3x3\n",
      "Conv2d_2a_3x3\n",
      "Conv2d_2b_3x3\n",
      "maxpool1\n",
      "Conv2d_3b_1x1\n",
      "Conv2d_4a_3x3\n",
      "maxpool2\n",
      "Mixed_5b\n",
      "Mixed_5c\n",
      "Mixed_5d\n",
      "Mixed_6a\n",
      "Mixed_6b\n",
      "Mixed_6c\n",
      "Mixed_6d\n",
      "Mixed_6e\n",
      "AuxLogits\n",
      "Mixed_7a\n",
      "Mixed_7b\n",
      "Mixed_7c\n",
      "avgpool\n",
      "dropout\n",
      "fc\n",
      "Desired layer not found\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "c:\\Users\\sunsh\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\torchvision\\models\\_utils.py:208: UserWarning: The parameter 'pretrained' is deprecated since 0.13 and may be removed in the future, please use 'weights' instead.\n",
      "  warnings.warn(\n",
      "c:\\Users\\sunsh\\AppData\\Local\\Programs\\Python\\Python310\\lib\\site-packages\\torchvision\\models\\_utils.py:223: UserWarning: Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and may be removed in the future. The current behavior is equivalent to passing `weights=Inception_V3_Weights.IMAGENET1K_V1`. You can also use `weights=Inception_V3_Weights.DEFAULT` to get the most up-to-date weights.\n",
      "  warnings.warn(msg)\n"
     ]
    }
   ],
   "source": [
    "import torch\n",
    "import torchvision.models as models\n",
    "\n",
    "# Load the InceptionV3 model\n",
    "model = models.inception_v3(pretrained=True)\n",
    "model.eval()\n",
    "\n",
    "# Accessing the desired layer\n",
    "desired_layer_name = \"Block1_Conv1\"  # Example layer name\n",
    "desired_layer = None\n",
    "\n",
    "# Iterate through model's named children to find the desired layer\n",
    "for name, layer in model.named_children():\n",
    "    print(name)\n",
    "    if desired_layer_name in name:\n",
    "        desired_layer = layer\n",
    "        break\n",
    "\n",
    "if desired_layer is None:\n",
    "    print(\"Desired layer not found\")\n",
    "else:\n",
    "    print(desired_layer)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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